Objective: The purpose of this study is to investigate the independent influencing factors of the transition from normal population to prediabetes, and from prediabetes to diabetes, and to further construct clinical prediction models to provide a basis for the prevention and management of prediabetes and diabetes.
Materials And Methods: The data for this study were based on clinical information of participants from the Health Management Center of Peking University Shenzhen Hospital. Participants were classified into normal group, prediabetes group, and diabetes group according to their functional status of glucose metabolism. Spearman's correlation coefficients were calculated for the variables, and a matrix diagram was plotted. Further, univariate and multivariate logistic regression analysis were conducted to explore the independent influencing factors. The independent influencing factors were used as predictors to construct the full-variable prediction model (Full.model) and simplified prediction model (Simplified.model).
Results: This study included a total of 5310 subjects and 22 variables, among which there were 1593(30%) in the normal group, 3150(59.3%) in the prediabetes group, and 567(10.7%) in the diabetes group. The results of the multivariable logistic regression analysis showed that there were significant differences in 9 variables between the normal group and the prediabetes group, including age(Age), body mass index(BMI), systolic blood pressure(SBP), urinary glucose(U.GLU), urinary protein(PRO), total protein(TP), globulin(GLB), alanine aminotransferase(ALT), and high-density lipoprotein cholesterol(HDL-C). There were significant differences in 7 variables between the prediabetes group and the diabetes group, including Age, BMI, SBP, U.GLU, PRO, triglycerides(TG), and HDL.C. The Full.model and Simplified.model constructed based on the above influencing factors had moderate discriminative power in both the training set and the test set.
Conclusion: Age, BMI, SBP, U.GLU, PRO, TP, and ALT are independent risk factors, while GLB and HDL.C are independent protective factors for the development of prediabetes in the normal population. Age, BMI, SBP, U.GLU, PRO, and TG are independent risk factors, while HDL.C is an independent protective factor for the progression from prediabetes to diabetes. The Full.model and Simplified.model developed based on these influencing factors have moderate discriminative power.
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http://dx.doi.org/10.3389/fendo.2023.1225696 | DOI Listing |
Biomater Adv
January 2025
Department of Orthopaedic Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, 600 Yishan Rd., Shanghai 200233, PR China. Electronic address:
Improving the regeneration of the tendon-bone interface (TBI) helps to decrease the risk of rotator cuff retears after repair surgeries. Unfortunately, the lack of inherent healing capacity of the TBI, insufficient mechanical properties, and abnormal and persistent inflammation during repair are the key factors leading to suboptimal healing of the rotator cuff. Therefore, a high-strength rotator cuff repair material capable of regulating the unbalanced immune response and enhancing the regeneration of the TBI is urgently needed.
View Article and Find Full Text PDFJ Radiol Prot
January 2025
Department of Biostatistics, Soon Chun Hyang University Hospital Bucheon, Bucheon, Gyeonggi-do, Korea (the Republic of).
This study investigated the additional radiation exposure, influencing factors, and clinical significance of overlapping Z-axis coverage in abdominopelvic CT scans performed consecutively after same-day chest CT scans. Data from 761 patients were analyzed, with measuring the total and overlapping Z-axis coverage of the portal venous phase in abdominopelvic CT scans. The average overlapping portion was 33.
View Article and Find Full Text PDFAnnu Rev Immunol
January 2025
3Department of Environmental Medicine and Department of Microbiology and Immunology, University of Rochester, Rochester, New York, USA; email:
Initially discovered for its role mediating the deleterious effects of environmental contaminants, the aryl hydrocarbon receptor (AHR) is now known to be a crucial regulator of the immune system. The expanding list of AHR ligands includes synthetic and naturally derived molecules spanning pollutants, phytochemicals, pharmaceuticals, and substances derived from amino acids and microorganisms. The consequences of engaging AHR vary, depending on factors such as the AHR ligand, cell type, immune challenge, developmental state, dose, and timing of exposure relative to the immune stimulus.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Public Health, Capital Medical University, Beijing, China.
Background: Health inequalities among older adults become increasingly pronounced as aging progresses. In the digital era, some researchers argue that access to and use of digital technologies may contribute to or exacerbate these existing health inequalities. Conversely, other researchers believe that digital technologies can help mitigate these disparities.
View Article and Find Full Text PDFTissue Eng Part C Methods
January 2025
Trinity Centre for Biomedical Engineering, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
Scaffold-free tissue engineering strategies using cellular aggregates, microtissues, or organoids as "biological building blocks" could potentially be used for the engineering of scaled-up articular cartilage or endochondral bone-forming grafts. Such approaches require large numbers of cells; however, little is known about how different chondrogenic growth factor stimulation regimes during cellular expansion and differentiation influence the capacity of cellular aggregates or microtissues to fuse and generate hyaline cartilage. In this study, human bone marrow mesenchymal stem/stromal cells (MSCs) were additionally stimulated with bone morphogenetic protein 2 (BMP-2) and/or transforming growth factor (TGF)-β1 during both monolayer expansion and subsequent chondrogenic differentiation in a microtissue format.
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